High sampling rate sensor buffering in semiconductor processing systems

ABSTRACT

Embodiments of the invention are directed toward systems and/or methods that buffer data from various sensors with a high sampling rate in a semiconductor processing system. Such sampling can provide better data about the processing for diagnosing the conditions leading up to a processing fault in the system.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application claims the benefit of U.S. Prov. Pat. App. No.61/658,622 filed Jun. 12, 2012, and titled “High Sampling Rate SensorBuffering in Semiconductor Processing Systems,” which is entirelyincorporated herein by reference for all purposes.

BACKGROUND OF THE INVENTION

Semiconductor processing systems are complex systems that perform avariety of complex processes. Because of the complexity of the systemsand/or processes faults can occur for any number of reasons related toeither hardware or software malfunction.

BRIEF SUMMARY OF THE INVENTION

The terms “invention,” “the invention,” “this invention” and “thepresent invention” used in this patent are intended to refer broadly toall of the subject matter of this patent and the patent claims below.Statements containing these terms should not be understood to limit thesubject matter described herein or to limit the meaning or scope of thepatent claims below. Embodiments of the invention covered by this patentare defined by the claims below, not this summary. This summary is ahigh-level overview of various aspects of the invention and introducessome of the concepts that are further described in the DetailedDescription section below. This summary is not intended to identify keyor essential features of the claimed subject matter, nor is it intendedto be used in isolation to determine the scope of the claimed subjectmatter. The subject matter should be understood by reference to theentire specification of this patent, all drawings and each claim.

Embodiments of the invention are directed toward systems and/or methodsthat buffer raw data received from one or more sensors with a highsample rate in a semiconductor processing system. Such sampling canprovide better data about the cause of a fault in the semiconductorprocessing system. Some embodiments of the invention include asemiconductor processing system with a plurality of sensors that measurevarious processing conditions, a buffer coupled to at least a subset ofthe plurality of sensors, and a long term storage device coupled withthe buffer. The buffer can be used to collect raw data from the subsetof sensors at a high sampling rate.

These illustrative embodiments are mentioned not to limit or define thedisclosure, but to provide examples to aid understanding thereof.Additional embodiments are discussed in the Detailed Description, andfurther description is provided there. Advantages offered by one or moreof the various embodiments may be further understood by examining thisspecification or by practicing one or more embodiments presented.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features, aspects, and advantages of the presentdisclosure are better understood when the following Detailed Descriptionis read with reference to the accompanying drawings.

Illustrative embodiments of the present invention are described indetail below with reference to the following drawing figures:

FIG. 1 is a block diagram of a Sensor system according to someembodiments of the invention.

FIG. 2 is a flowchart of a process for buffering sensor data accordingto some embodiments of the invention.

FIG. 3 illustrates an example arc detection system according to someembodiments of the invention.

FIG. 4 illustrates another example arc detection system according tosome embodiments of the invention.

FIG. 5 shows a simplified block diagram of a computational system thatcan be used to implement embodiments of the invention.

DETAILED DESCRIPTION OF THE INVENTION

The subject matter of embodiments of the invention is described herewith specificity to meet statutory requirements, but this description isnot necessarily intended to limit the scope of the claims. The claimedsubject matter may be embodied in other ways, may include differentelements or steps, and may be used in conjunction with other existing orfuture technologies. This description should not be interpreted asimplying any particular order or arrangement among or between varioussteps or elements except when the order of individual steps orarrangement of elements is explicitly described.

Semiconductor manufacturing systems can fail due to hardware or softwaremalfunction. Many faults can be hard to troubleshoot because someinformation, such as a given sensor's state can be lost at the time ofthe fault. Depending on the fault, sensor information can be useful indiagnosing the cause of the fault. Embodiments of the invention can beused to buffer sensor data at a high sample rate to ensure sensorinformation is available to diagnose the fault.

Embodiments of the invention are directed toward systems and/or methodsthat buffer data from various sensors with a high sampling rate in asemiconductor processing system. Such sampling can provide better dataabout the processing for diagnosing the conditions leading up to aprocessing fault in the system.

FIG. 1 shows a block diagram of sensor system 100 according to someembodiments of the invention. Sensor system 100 can be used, forexample, in any processing system; for example, semiconductor processingsystems, solar array processing systems, display processing systems,battery processing systems, etc. As other examples, sensor system 100can be used in various stages or portions of a processing system such asin front-of-the-line processes, deposition processes, removal processes,etching processes, patterning processes, modification processes, threedimensional printing processes, back-of-the-line processes, wafertesting, among others. For example, depositions processes can includephysical vapor deposition (PVD), chemical vapor deposition (CVD),electrochemical deposition (ECD), molecular beam epitaxy (MBE), and/oratomic layer deposition (ALD) systems among others. Removal processes,for example, can include wet etching, dry etching, and/orchemical-mechanical planarization (CMP) among others. Patterningprocesses, for example, can include conventional lithography,photolithography, stepper processes, and/or plasma ashing among others.Modification processes, for example, can include doping processes,thermal oxidation, and/or annealing (including rapid thermal annealingamong others.

Sensor system 100 can include buffer 105 coupled with hard drive 110.Buffer 105 can include inputs that can be electrically connected with asensor such as, for example, sensor 120, sensor 121, and/or sensor 122.Connectors can also be used to connect one or more sensors with one ormore buffer inputs. Controller 140 can be used to control operation ofbuffer 105 and/or hard drive 110.

Buffer 105 can be any memory that temporarily stores sensor data priorto being stored in hard drive 110. Buffer 105 can comprise any type ofmemory device, such as, for example, RAM. Buffer 105 can comprise asingle buffer coupled with a plurality of sensors, or a single a buffercoupled with a single sensor. Moreover, buffer 105 can include aplurality of buffers each of which are coupled with one of a pluralityof sensors.

In some embodiments, in operation, buffer 105 can store raw sensor data,which may be digitized. This raw sensor data may or may not includeprocessing information. Buffer 105 may also store a counter or timingdata within buffer 105. Processing information can the data collectiontime, date information, sensor information, processing systeminformation, tool information, processing recipe information,fabrication information, processing location, operator information, dataunits, etc. When the raw sensor data is written to hard drive 110, thesensor data can be stored in conjunction with any or all processinginformation.

Moreover, when the raw sensor data is written to hard drive 110, the rawsensor data can be formatted to a predetermined or selectable formattingstyle. Often sensors produce raw sensor data as a voltage, resistance,or other raw value. In such cases, the raw sensor data may be convertedfrom the raw value to a physically meaningful value using an equationand/or a table. For example, a temperature sensor may include athermocouple that produces a voltage. In operation, the voltage of thethermocouple can be sampled and stored in buffer 105 at a high samplingrate. Controller 140 can convert the voltage value stored in buffer 105to a temperature value using an equation and/or table.

In operation, buffer 105 can store raw sensor data from one or moresensors at a rate that is faster than one hundred bits per microsecond,ten bits per microsecond or one bit per microsecond. This sampling rateof buffer 105, for example, can be a higher than the sampling rate ofhard drive 110. Various other components can be included in Sensorsystem 100; for example, an analog to digital converter(s) can bedisposed between sensors and buffer 105 to digitize analog sensor data.

For example, buffer 105 may include two buffers each of which areassigned to separate sensors. For example, one buffer may buffer datafrom a temperature sensor and another may buffer raw data from a flowsensor. In embodiments with a plurality of sensors a plurality ofbuffers may be used.

In other embodiments, a single buffer may be used. For example, atemperature sensor and a flow sensor may be coupled to the singlebuffer. The raw temperature sensor data may be stored in a first bufferlocation as a raw resistance value and the raw flow data may be storedat a second buffer storage location as a raw voltage value. In someembodiments, when writing the buffered data to hard drive 110, the rawresistance value can be converted to temperature prior to being storedin the hard drive using controller 140. In other embodiments, the rawvalue can be stored in hard drive 110.

In some embodiments raw sensor data may also be stored in the hard drivewith a time stamp (or counter) that associates the data or each dataelement to the time the data was collected based, for example, on thetime the data started being recorded, the number of samples buffered,and the sampling rate. Any of the other processing information,described above or otherwise, may also be stored in the hard drive alongwith the sampled data. Furthermore, the raw data may be formatted, forexample, to fit within a table, to have a specific length in bits orbytes, marked up, assigned some type of informational tag, etc.

In some embodiments, buffer 105 can write data collected from thesensors to the hard drive while the processing system is operating. Inother embodiments, buffer 105 can collect data continuously and writethe collected data to the hard drive after a fault has been detected. Inthis embodiment, while data is being collected, older data is beingdeleted from the buffer. To ensure enough data is collected, buffer 105may be required to have sufficient memory to capture and buffer thecollected data for a required period of time, for example, 5, 10, 15,20, 25, 30, 35, 40, 45, 50, 55, or 60 minutes. Regardless, in someembodiments, at some point data stored in buffer 105 from one or moresensors can be stored in hard drive 110.

Hard drive 110 can include any type of long term storage device. Forexample, hard drive 110 can comprise a storage server, RAM, cloudstorage, etc.

The sensors, sensor 120, sensor 121, and/or sensor 122, can include anytype of sensor. For example, one or more sensor can measure atmosphericconditions within a processing chamber such as temperature, humidity, orpressure. As another example, one or more sensors can measure gas flowsinto and/or out of the process chamber, DC power to the chamber, DCpower within the chamber, RF power within the chamber, current draw,etc. As another example, one or more sensors can measure the positionand/or movement of various components such as substrate supportstructures, substrate carriers, and/or other tooling components.Moreover, as another example, sensors can measure the torque and/orspeed of various motors. As yet another example, one or more sensors canmeasure any of various environmental conditions such as heat, radiation,sounds and/or vibrations. As another example, one or more sensors cansense the pressure, flow, temperature, and/or amount of chemicals and/orgases within the processing chamber, within conduits, and/or withintanks. As yet another example, one or more sensors can measure variousprocessing conditions such as wafer thicknesses, wafer sizes, waferuniformity, wafer polishing etc. Various other sensors can be usedwithout limitation.

Sensor system 100 may also include output 135 that can be used toprovide the sensor information. This can be done by any technique knownin the art; for example, the data can be emailed to an engineer orscientist of the facility or manufacturer. As another example, the datacan be stored in a file located at a computer system or at a cloudstorage location. The data can then be accessed by an operator, engineeror scientist through a computer network (e.g., the Internet).

FIG. 2 shows a flowchart of process 200 for buffering sensor dataaccording to some embodiments of the invention. Process 200 begins atblock 205. At block 210 sensor data can be written to the buffer. Thissensor data can be collected from at least one of multiple sensors(e.g., sensors 120, 121, and/or 122). This sensor data can be written tothe buffer with fast sample rates. At block 215 data from the buffer canbe written to a hard drive. This can occur at a rate slower than therate that the data is written to the buffer from the sensors, and/orsome data can be written to hard drive 110 while other data is beingwritten to buffer 105.

At block 220 it can be determined if a fault has occurred. This canhappen in a number of ways. For example, an engineer managing theprocessing system (or any other worker) can manually determine a faulthas occurred, or the processing system can determine a fault hasoccurred based on data from one or more sensors within the system. If nofault is determined, then process 200 returns to blocks 210 and 215. Ifa fault is determined, regardless of how it is determined, process 200proceeds to block 225 and the data recorded in the hard drive is outputto a user. This can be done in any number of ways. In some embodimentsit may be required to wait for the data to be written from the buffer tothe hard drive before outputting the data to a user to ensure all thedata has been written to the hard drive. Process 200 can end at block230.

FIG. 3 shows an example of a processing system 300 that may be used inembodiments of the invention. Processing system 300 may include a pairof FOUPs (front opening unified pods) 302 to supply substrates (e.g.,300 mm diameter wafers) that are received by robotic arms 304 and placedinto a low pressure holding area before being placed into one of thewafer processing chambers 307 a-f. Each processing chamber 307 a-f canbe outfitted to perform a number of substrate processing operationsincluding the remote plasma processes described herein in addition tocyclical layer deposition (CLD), atomic layer deposition (ALD), chemicalvapor deposition (CVD), PVD, etch, pre-clean, degas, orientation andother substrate processes.

The processing chambers 307 a-f may include one or more systemcomponents for depositing, annealing, curing and/or etching on thesubstrate wafer. In one configuration, two pairs of the processingchamber (e.g., 307 c-d and 307 e-f) may be used to deposit dielectricmaterial on the substrate, and the third pair of processing chambers(e.g., 307 a-b) may be used to etch the deposited dielectric. In anotherconfiguration, all three pairs of chambers (e.g., 307 a-f) may beconfigured to provide an etching process on the substrate. Any one ormore of the processes described may be carried out on chamber(s)separated from the fabrication system shown in different embodiments.

Each processing chamber (e.g., 307 a) may include a substrate support(e.g., 308 a) configured to support a substrate within a processingchamber during a process. For example, substrate support 308 a may be anelectrostatic chuck (ESC) which holds and supports the substrate withinthe processing chamber 307 a. In addition to a substrate support, eachprocessing chamber (e.g., 307 a) may also include at least one sensor(e.g., 309 a) configured to measure one or more critical parametersassociated with a substrate processing that takes place within theprocessing chamber (e.g., 307 a) to generate an analog output signalrepresentative of the measured parameters.

System controller 310 is used to control motors, valves, flowcontrollers, power supplies and other functions required to carry outprocess recipes by the processing system. System controller 310 may relyon feedback from optical sensors to determine and adjust the position ofmovable mechanical assemblies in processing chambers 307 a-f. Mechanicalassemblies may include the robot, throttle valves and susceptors whichare moved by motors under the control of system controller 310. Systemcontroller 310 can include sensor system 100.

In some embodiments, system controller 310 includes memory (e.g., a harddisk drive), input and output ports, and a processor. System controller310 may include analog and digital input/output boards, interfaceboards, and stepper motor controller boards. Various parts ofmulti-chamber processing system are controlled by system controller 310.The system controller executes system control software in the form of acomputer program stored on computer-readable medium such as a hard disk,a floppy disk or a flash memory thumb drive. Other types of memory canalso be used. The computer program includes sets of instructions thatdictate the timing, mixture of gases, chamber pressure, chambertemperature, RF power levels, susceptor position, and other parametersof a particular process.

Processing chamber (e.g., 307 a) can be any type of processing chamber.One example is a PECVD chamber shown in FIG. 4. PECVD chamber 400includes sidewalls 402, a bottom wall 404, and a chamber lid 406, whichcumulatively define a processing region 408. A gas distribution system410 is disposed through the chamber lid 406 to deliver gases into theprocessing region 408. The gas distribution system 410 includes a gasbox 412 with a gas inlet 414 that receives processing gases from aprecursor source 411 and that introduces processing gases into the gasbox 412. The gas distribution system 410 also includes a showerhead 416having a plurality of gas passages 418 for distributing the processinggases from the gas box 412 into the processing region 408. The gasdistribution system 410 may also include a gas box heater 420, such as aring-shaped, resistive heater, to heat processing gases to a desiredtemperature.

The showerhead 416 is coupled to an RF power supply 422 to provideelectrical energy to the showerhead 416 to facilitate plasma formationin the processing region 408. Thus, the showerhead 416 acts as an upper,powered electrode. An auto-tuned RF matching network 424 is positionedbetween the RF power supply 422 and the showerhead 416. In oneembodiment, the RF power is supplied at a frequency of about 23.56 M Hz.

The bottom wall 404 defines a passage 426 for a stem 428 that supports apedestal heater 430. The pedestal heater 430 is configured to support asubstrate 401 in the processing region 408. The pedestal heater 430includes a ground mesh 432 embedded therein, which is connected to an RFground. Thus, the ground mesh 432 acts as a ground electrode tofacilitate plasma formation in the processing region 408 between theshowerhead 416 and the pedestal heater 430. The pedestal heater 430 alsoincludes one or more heating elements 434, such as resistive heatingelements, to heat the substrate 401 to a desired processing temperature.

A control system 450, including a central processing unit (CPU) 452, amemory 454 and support circuits 456, is coupled to the variouscomponents of the chamber 400 to facilitate control of processing withinthe chamber 400. The memory 454 can be any computer-readable medium,such as random access memory (RAM), read only memory (ROM), floppy disk,hard disk, or any other form of digital storage, local or remote to thechamber 400 or CPU 452. The support circuits 456 are coupled to the CPU452 for supporting the CPU 452 in a conventional manner. These circuitsinclude cache, power supplies, clock circuits, input/output circuitryand subsystem, and the like. A software routine or a series of programinstructions store in the memory 454, when executed by the CPU 452,causes the chamber 400 to perform plasma processes therein. Controlsystem 450 may also include sensor system 100.

Deposition chambers that may benefit from the present invention includechambers configured to deposit oxides, such as carbon-doped siliconoxides, silicon containing films, and other dielectric materialsincluding advanced patterned films (APF). An example of a depositionchamber is the PRODUCER™ chamber available from Applied Materials, Inc.of Santa Clara, Calif. The PRODUCER™ chamber is a PECVD chamber with twoisolated processing regions that may be used to deposit carbon-dopedsilicon oxides and other materials. An example of a chamber is describedin U.S. Pat. No. 5,855,681, which is incorporated herein by reference inits entirety. Although the chamber 400 is schematically depicted as aPECVD chamber, use of the invention may be equally affective on otherchambers, such as plasma etch, PVD, or any other type of chamber.

The computer system 500, shown in FIG. 5 can be used to perform any ofthe embodiments of the invention. For example, computer system 500 canbe used to execute method 200. As another example, sensor system 300 caninclude all or parts of computer system 500. As yet another example,computer system 500 can be used to perform any calculation,identification and/or determination described here. Computer system 500includes hardware elements that can be electrically coupled via a bus505 (or may otherwise be in communication, as appropriate).

Computer system 500 is shown having hardware elements that areelectrically coupled via bus 526. Network interface 552 cancommunicatively couple the computational device 500 with anothercomputer, for example, through a network such as the Internet. Thehardware elements can include a controller 340, an input device 504, anoutput device 506, a hard drive 340, a computer-readable storage mediareader 510 a, a communications system 514, a processing accelerationunit 516 such as a DSP or special-purpose processor, and memory 518. Thecomputer-readable storage media reader 510 a can be further connected toa computer-readable storage medium 510 b, the combinationcomprehensively representing remote, local, fixed, and/or removablestorage devices plus storage media for temporarily and/or morepermanently containing computer-readable information. Buffer 305 iscoupled with bus 526.

Computer system 500 can also comprise software elements, shown as beingcurrently located within working memory 520, including an operatingsystem 524 and other code 522, such as a program designed to implementmethods and/or processes described herein. In some embodiments, othercode 522 can include software that provides instructions for receivinguser input from a dual polarization radar system and manipulating thedata according to various embodiments disclosed herein. In someembodiments, any software elements or code may be non-transitory. Itwill be apparent to those skilled in the art that substantial variationscan be used in accordance with specific requirements. For example,customized hardware might also be used and/or particular elements mightbe implemented in hardware, software (including portable software, suchas applets), or both. Further, connection to other computing devicessuch as network input/output devices can be employed.

The computational system 500 may further include (and/or be incommunication with) one or more storage devices 525, which can include,without limitation, local and/or network accessible storage and/or caninclude, without limitation, a disk drive, a drive array, an opticalstorage device, a solid-state storage device, such as a random accessmemory (“RAM”) and/or a read-only memory (“ROM”), which can beprogrammable, flash-updateable and/or the like. The computational system500 might also include a communications subsystem 530, which can includewithout limitation a modem, a network card (wireless or wired), aninfrared communication device, a wireless communication device and/orchipset (such as a Bluetooth device, an 802.6 device, a WiFi device, aWiMax device, cellular communication facilities, etc.), and/or the like.The communications subsystem 530 may permit data to be exchanged with anetwork (such as the network described below, to name one example),and/or any other devices described herein. In many embodiments, thecomputational system 500 will further include a working memory 535,which can include a RAM or ROM device, as described above.

The computational system 500 also can include software elements, shownas being currently located within the working memory 535, including anoperating system 540 and/or other code, such as one or more applicationprograms 545, which may include computer programs of the invention,and/or may be designed to implement methods of the invention and/orconfigure systems of the invention, as described herein. For example,one or more procedures described with respect to the method(s) discussedabove might be implemented as code and/or instructions executable by acomputer (and/or a processor within a computer). A set of theseinstructions and/or codes might be stored on a computer-readable storagemedium, such as the storage device(s) 525 described above.

In some cases, the storage medium might be incorporated within thecomputational system 500 or in communication with the computationalsystem 500. In other embodiments, the storage medium might be separatefrom a computational system 500 (e.g., a removable medium, such as acompact disc, etc.), and/or provided in an installation package, suchthat the storage medium can be used to program a general purposecomputer with the instructions/code stored thereon. These instructionsmight take the form of executable code, which is executable by thecomputational system 500 and/or might take the form of source and/orinstallable code, which, upon compilation and/or installation on thecomputational system 500 (e.g., using any of a variety of generallyavailable compilers, installation programs, compression and/ordecompression utilities, etc.) then takes the form of executable code.

Different arrangements of the components depicted in the drawings ordescribed above, as well as components and steps not shown or describedare possible. Similarly, some features and subcombinations are usefuland may be employed without reference to other features andsubcombinations. Embodiments of the invention have been described forillustrative and not restrictive purposes, and alternative embodimentswill become apparent to readers of this patent. Accordingly, the presentinvention is not limited to the embodiments described above or depictedin the drawings, and various embodiments and modifications can be madewithout departing from the scope of the claims below.

Numerous specific details are set forth herein to provide a thoroughunderstanding of the claimed subject matter. However, those skilled inthe art will understand that the claimed subject matter may be practicedwithout these specific details. In other instances, methods, apparatusesor systems that would be known by one of ordinary skill have not beendescribed in detail so as not to obscure claimed subject matter.

Some portions are presented in terms of algorithms or symbolicrepresentations of operations on data bits or binary digital signalsstored within a computing system memory, such as a computer memory.These algorithmic descriptions or representations are examples oftechniques used by those of ordinary skill in the data processing artsto convey the substance of their work to others skilled in the art. Analgorithm is a self-consistent sequence of operations or similarprocessing leading to a desired result. In this context, operations orprocessing involves physical manipulation of physical quantities.Typically, although not necessarily, such quantities may take the formof electrical or magnetic signals capable of being stored, transferred,combined, compared or otherwise manipulated. It has proven convenient attimes, principally for reasons of common usage, to refer to such signalsas bits, data, values, elements, symbols, characters, terms, numbers,numerals or the like. It should be understood, however, that all ofthese and similar terms are to be associated with appropriate physicalquantities and are merely convenient labels. Unless specifically statedotherwise, it is appreciated that throughout this specificationdiscussions utilizing terms such as “processing,” “computing,”“calculating,” “determining,” and “identifying” or the like refer toactions or processes of a computing device, such as one or morecomputers or a similar electronic computing device or devices, thatmanipulate or transform data represented as physical electronic ormagnetic quantities within memories, registers, or other informationstorage devices, transmission devices, or display devices of thecomputing platform.

The system or systems discussed herein are not limited to any particularhardware architecture or configuration. A computing device can includeany suitable arrangement of components that provides a resultconditioned on one or more inputs. Suitable computing devices includemultipurpose microprocessor-based computer systems accessing storedsoftware that programs or configures the computing system from a generalpurpose computing apparatus to a specialized computing apparatusimplementing one or more embodiments of the present subject matter. Anysuitable programming, scripting, or other type of language orcombinations of languages may be used to implement the teachingscontained herein in software to be used in programming or configuring acomputing device.

Embodiments of the methods disclosed herein may be performed in theoperation of such computing devices. The order of the blocks presentedin the examples above can be varied—for example, blocks can bere-ordered, combined, and/or broken into sub-blocks. Certain blocks orprocesses can be performed in parallel.

The use of “adapted to” or “configured to” herein is meant as open andinclusive language that does not foreclose devices adapted to orconfigured to perform additional tasks or steps. Additionally, the useof “based on” is meant to be open and inclusive, in that a process,step, calculation, or other action “based on” one or more recitedconditions or values may, in practice, be based on additional conditionsor values beyond those recited. Headings, lists, and numbering includedherein are for ease of explanation only and are not meant to belimiting.

While the present subject matter has been described in detail withrespect to specific embodiments thereof, it will be appreciated thatthose skilled in the art, upon attaining an understanding of theforegoing, may readily produce alterations to, variations of, andequivalents to such embodiments. Accordingly, it should be understoodthat the present disclosure has been presented for purposes of examplerather than limitation, and does not preclude inclusion of suchmodifications, variations and/or additions to the present subject matteras would be readily apparent to one of ordinary skill in the art.

That which is claimed:
 1. A semiconductor processing system comprising:a plurality of sensors that measure physical conditions of thesemiconductor processing system; a buffer electrically coupled with atleast a subset of the plurality of sensors to store sensor data at afirst sampling rate; a long term storage device electrically coupledwith the buffer to store data stored at the buffer and wherein the longterm storage device has a second sampling rate that is less than thefirst sampling rate of the buffer; and a controller electrically coupledto the buffer and the long term storage device, wherein the controlleris configured to cause the sensor data stored at the buffer to be storedinto the long term storage device at or below the second sampling ratethat is less than the first sampling rate, and the controller isconfigured to, in response to a fault event, automatically output datastored in the long term storage device to a user.
 2. The semiconductorprocessing system according to claim 1, wherein at least two of theplurality of sensors measure different physical conditions of thesemiconductor processing system.
 3. The semiconductor processing systemaccording to claim 1, further comprising an analog to digital convertercoupled between at least one sensor of the plurality of sensors and thebuffer, the analog to digital converter configured to sample and convertsensor signals from the at least one sensor of the plurality of sensorsinto the sensor data.
 4. The semiconductor processing system accordingto claim 1, wherein the buffer comprises a plurality of buffers.
 5. Thesemiconductor processing system according to claim 1, wherein the buffercomprises RAM.
 6. The semiconductor processing system according to claim1, wherein the buffer stores the sensor data at a rate greater than 1bit per microsecond.
 7. The semiconductor processing system according toclaim 1, wherein the buffer stores the sensor data at a rate greaterthan 100 bits per microsecond.
 8. The semiconductor processing systemaccording to claim 1, wherein the controller is further configured toformat the sensor data before storing the sensor data stored at thebuffer into the long term storage device.
 9. The semiconductorprocessing system according to claim 1, wherein the controller isconfigured to store processing information associated with the sensordata when storing the sensor data stored at the buffer into the longterm storage device, and wherein the processing information includes atleast one of sensor information, processing system information, toolinformation, processing recipe information, fabrication information,processing location, or operator information.
 10. The semiconductorprocessing system according to claim 1, wherein the long term storagedevice is configured to store a time stamp associated with the sensordata when storing the sensor data stored at the buffer.
 11. A method forsensing environmental conditions in a semiconductor processing system,the method comprising: storing sensor data in a buffer at a firstsampling rate; receiving a fault event; and in response to receiving thefault event: storing the sensor data stored in the buffer into a harddrive at a second sampling rate that is less than the first samplingrate; and automatically outputting data stored in the hard drive to auser.
 12. The method according to claim 11, further comprising receivingsensors data from at least two sensors that measure different physicalconditions of the semiconductor processing system.
 13. The methodaccording to claim 11, further comprising sampling and converting sensorsignals from at least one sensor of the plurality of sensors at thefirst sampling rate using an analog to digital converter coupled betweenthe at least one sensor of the plurality of sensors and the buffer. 14.The method according to claim 11, wherein the buffer comprises aplurality of buffers.
 15. The method according to claim 11, wherein thebuffer comprises RAM.
 16. The method according to claim 11, whereinsensor data is stored in the buffer at a sampling rate greater than 1bit per microsecond.
 17. The method according to claim 11, whereinsensor data is stored in the buffer at a sampling rate greater than 100bits per microsecond.
 18. The method according to claim 11, wherein thesensor data is stored into the hard drive with a time stamp or aprocessing information associated with the sensor data, and wherein theprocessing information includes at least one of sensor information,processing system information, tool information, processing recipeinformation, fabrication information, processing location, or operatorinformation.
 19. The method according to claim 11, further comprising:formatting the sensor data before storing the sensor data stored at thebuffer into the hard drive.
 20. The method according to claim 19,wherein formatting the sensor data includes at least one of fitting thesensor data within a table, formatting the sensor data to have aspecific lengths in bits or bytes, marking the sensor data, assigningtags to the sensor data, or converting electrical signal values intotemperature values.